Main
Shixiang Wang
PhD student of Bioinformatics at Xue-Song Liu lab, ShanghaiTech University, currently working on cancer genomics and immunotherapy biomarker by biostatistic skills. I am a fan of R (particularly), Python and Golang. I love open source and open science. I have developed many R package and shared much experience about coding and data analysis on many platforms.
For some details,
- I have advanced experience in using R and Shell for data preprocessing, data cleaning and data interpretation.
- I have moderate experience in using R for statistical modeling and data visualization.
- I master developing pure R packages and have a little experience in Python package, R Shiny and Rcpp development.
- I can combine multiple programming languages/tools to create analysis pipeline. I know how to use Docker to package analysis environment and enhance reproducible research.
- I can process raw genomic data and analyze them. I have moderate experience in somatic variant calling (including SNV, INDEL and CNV), differential expression analysis and enrichment analysis.
- I know how to do machine learning (including deep learning) and have applied some technologies to my projects.
- I like to write with R Markdown (including Markdown) and share my knowledge to others in many ways.
- I love to contribute open-source scientific tool development (e.g. maftools, forestmodel).
- Last not but least, I enjoy learning and researching.
Education
PhD., Biology
ShanghaiTech University
Shanghai, CN
2021 - 2016
PhD., Biology
University of Chinese Academy of Sciences
Beijing, CN
PhD., Biology
Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences
Shanghai, CN
B.E., Biomedical Engineering
University of Electronic Science and Technology of China
Chengdu, CN
2016 - 2012
Publications
- Citation = 150
- H-index = 4
- I10-index = 4
Sigflow: an automated and comprehensive pipeline for cancer genome mutational signature analysis
Bioinformatics (2020)
N/A
2020
- Wang, S., Tao, Z., Wu, T., & Liu, X. S.*
Can tumor mutational burden determine the most effective treatment for lung cancer patients?
LUNG CANCER MANAGEMENT (2020)
N/A
- Wang, S., He, Z., Wang, X., Li, H., Wu, T., Sun, X., … & Liu, X. S.*
Antigen presentation and tumor immunogenicity in cancer immunotherapy response prediction
Elife (2019)
N/A
2019
- Wang, S., He, Z., Wang, X., Li, H., & Liu, X. S.*
The predictive power of tumor mutational burden in lung cancer immunotherapy response is influenced by patients’ sex
International journal of cancer (2019)
N/A
- Wang, S., Zhang, J., He, Z., Wu, K., & Liu, X. S.*
Ras Downstream Effector GGCT Alleviates Oncogenic Stress
iScience (2019)
N/A
- He, Z.#, Wang, S.#, Shao, Y.#, Zhang, J.#, Wu, X., Chen, Y., … & Liu, X. S.*
Sex Differences in Cancer Immunotherapy Efficacy, Biomarkers, and Therapeutic Strategy
Molecules (2019)
N/A
- Wang, S.#, Cowley, L. A.#, & Liu, X. S.*
The UCSCXenaTools R package: a toolkit for accessing genomics data from UCSC Xena platform, from cancer multi-omics to single-cell RNA-seq
Journal of Open Source Software (2019)
N/A
- Wang, S., & Liu, X. S.*
APOBEC3B and APOBEC mutational signature as potential predictive markers for immunotherapy response in non-small cell lung cancer
Oncogene (2018)
N/A
2018
- Wang, S.#, Jia, M.#, He, Z., & Liu, X. S.*
Conference proceedings
Sigflow: an automated and comprehensive pipeline for cancer genome mutational signature analysis
Shanghai, CN
2020
- Wang, S., Tao, Z., Li, H. M., Wu, T., & Liu, X. S.*
Antigen presentation and tumor immunogenicity in cancer immunotherapy response prediction
BioForum 2019 at ShanghaiTech University
Shanghai, CN
2019
- Wang, S., He, Z., Wang, X., Li, H., & Liu, X. S.*